Test-Driven Development

Philosophy

Core principle: Tests should verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn’t.

Good tests are integration-style: they exercise real code paths through public APIs. They describe what the system does, not how it does it. A good test reads like a specification – “user can checkout with valid cart” tells you exactly what capability exists. These tests survive refactors because they don’t care about internal structure.

Bad tests are coupled to implementation. They mock internal collaborators, test private methods, or verify through external means (like querying a database directly instead of using the interface). The warning sign: your test breaks when you refactor, but behavior hasn’t changed. If you rename an internal function and tests fail, those tests were testing implementation, not behavior.

Read references/tests.md for test naming rules and examples when writing tests. Read references/mocking.md for when and how to mock. Read references/test-tiers.md for organizing unit vs component tests. Read references/component-testing.md for UI component testing patterns.

Task Analysis

Two legitimate TDD styles. Pick one per feature; don’t mix mid-feature. Actively classify the task before writing any tests.

Step 1 — Check for explicit request

If user said “classical”, “Detroit”, or “inside-out” → Classical. Done. If user said “outside-in”, “London”, “mockist”, or “double-loop” → Outside-in. Done.

Otherwise, proceed to Step 2.

Step 2 — Examine task and codebase

• Entry point — where does the change enter? (UI component, route, API handler, domain service, utility)
• Scope — single module or crosses multiple layers?
• Collaborators — existing with stable interfaces, or new ones to discover?
• Task language — user-visible behavior (“user can…”) or internal logic (“calculate”, “transform”)?

Outside-in when ANY:

• Entry point is UI / route / controller
• Spans 2+ layers with new collaborators to discover
• Describes user journey or end-to-end flow
• Greenfield multi-component feature

Classical when:

• Single module with existing interface
• Algorithms, data transforms, domain rules
• Integrating with existing deep modules
• No outside-in signals

Default: classical when ambiguous. Outside-in requires discipline to replace mocks with real implementations; classical has no such cleanup tax.

Step 3 — State classification

Before proceeding, copy the template from assets/classification-template.md, fill it in, and present it to the user. Wait for user confirmation before writing any tests.

Anti-Pattern: Horizontal Slices

DO NOT write all tests first, then all implementation. This is “horizontal slicing” – treating RED as “write all tests” and GREEN as “write all code.”

This produces crap tests:

• Tests written in bulk test imagined behavior, not actual behavior
• You end up testing the shape of things (data structures, function signatures) rather than user-facing behavior
• Tests become insensitive to real changes – they pass when behavior breaks, fail when behavior is fine
• You outrun your headlights, committing to test structure before understanding the implementation

Correct approach: Vertical slices via tracer bullets. One test → one implementation → repeat. Each test responds to what you learned from the previous cycle. Because you just wrote the code, you know exactly what behavior matters and how to verify it.

WRONG (horizontal):
  RED:   test1, test2, test3, test4, test5
  GREEN: impl1, impl2, impl3, impl4, impl5

RIGHT (vertical):
  RED→GREEN: test1→impl1
  RED→GREEN: test2→impl2
  RED→GREEN: test3→impl3
  ...

Workflow (Classical / Inside-Out)

1. Planning

Using the entry point and scope identified in Task Analysis:

• Confirm with user what interface changes are needed
• Confirm with user which behaviors to test (prioritize)
• Identify opportunities for deep modules (small interface, deep implementation)
• Design interfaces for testability
• List the behaviors to test (not implementation steps)
• Get user approval on the plan

Ask: “What should the public interface look like? Which behaviors are most important to test?”

You can’t test everything. Confirm with the user exactly which behaviors matter most. Focus testing effort on critical paths and complex logic, not every possible edge case.

2. Tracer Bullet

Write ONE test that confirms ONE thing about the system:

RED:   Write test for first behavior → test fails
GREEN: Write minimal code to pass → test passes

This is your tracer bullet – proves the path works end-to-end.

3. Incremental Loop

For each remaining behavior:

RED:   Write next test → fails
GREEN: Minimal code to pass → passes

Rules:

• One test at a time
• Only enough code to pass current test
• Don’t anticipate future tests
• Keep tests focused on observable behavior

4. Refactor

After all tests pass, read references/refactoring.md and look for refactor candidates:

• Extract duplication
• Deepen modules (move complexity behind simple interfaces)
• Apply SOLID principles where natural
• Consider what new code reveals about existing code
• Run tests after each refactor step

Never refactor while RED. Get to GREEN first.

Checklist Per Cycle

[ ] Test describes behavior, not implementation
[ ] Test uses public interface only
[ ] Test would survive internal refactor
[ ] Code is minimal for this test
[ ] No speculative features added

When using outside-in TDD, read references/outside-in.md for the full double-loop workflow. When deciding test file placement, read references/test-tiers.md for unit vs component tier rules. When testing UI components, read references/component-testing.md for mount helpers and boundary faking patterns.

Validation

To validate changes to this skill, run the 4-stage process: discovery validation (test frontmatter triggers), logic validation (simulate execution), edge case testing (attack the logic), and architecture refinement (enforce progressive disclosure). See skills best practices for prompts.